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Abstract Rice is a vital staple crop, sustaining over half of the global population, and is a key model for genetic research. To support the growing need for comprehensive and accessible rice genomic data, GrameneOryza (https://oryza.gramene.org) was developed as an online resource adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data management. It distinguishes itself through its comprehensive multispecies focus, encompassing a wide variety of Oryza genomes and related species, and its integration with FAIR principles to ensure data accessibility and usability. It offers a community curated selection of high-quality Oryza genomes, genetic variation, gene function, and trait data. The latest release, version 8, includes 28 Oryza genomes, covering wild rice and domesticated cultivars. These genomes, along with Leersia perrieri and seven additional outgroup species, form the basis for 38 K protein-coding gene family trees, essential for identifying orthologs, paralogs, and developing pan-gene sets. GrameneOryza’s genetic variation data features 66 million single-nucleotide variants (SNVs) anchored to the Os-Nipponbare-Reference-IRGSP-1.0 genome, derived from various studies, including the Rice Genome 3 K (RG3K) project. The RG3K sequence reads were also mapped to seven additional platinum-quality Asian rice genomes, resulting in 19 million SNVs for each genome, significantly expanding the coverage of genetic variation beyond the Nipponbare reference. Of the 66 million SNVs on IRGSP-1.0, 27 million acquired standardized reference SNP cluster identifiers (rsIDs) from the European Variation Archive release v5. Additionally, 1200 distinct phenotypes provide a comprehensive overview of quantitative trait loci (QTL) features. The newly introduced Oryza CLIMtools portal offers insights into environmental impacts on genome adaptation. The platform’s integrated search interface, along with a BLAST server and curation tools, facilitates user access to genomic, phylogenetic, gene function, and QTL data, supporting broad research applications. Database URL: https://oryza.gramene.org 

Critical review of point of care devices in oral care. 

Abstract The protein–ligand binding affinity quantifies the binding strength between a protein and its ligand. Computer modeling and simulations can be used to estimate the binding affinity or binding free energy using data- or physics-driven methods or a combination thereof. Here we discuss a purely physics-based sampling approach based on biased molecular dynamics simulations. Our proposed method generalizes and simplifies previously suggested stratification strategies that use umbrella sampling or other enhanced sampling simulations with additional collective-variable-based restraints. The approach presented here uses a flexible scheme that can be easily tailored for any system of interest. We estimate the binding affinity of human fibroblast growth factor 1 to heparin hexasaccharide based on the available crystal structure of the complex as the initial model and four different variations of the proposed method to compare against the experimentally determined binding affinity obtained from isothermal titration calorimetry experiments. 

Abstract Human acidic fibroblast growth factor (hFGF1) is an all beta-sheet protein that is involved in the regulation of key cellular processes including cell proliferation and wound healing. hFGF1 is known to aggregate when subjected to thermal unfolding. In this study, we investigate the equilibrium unfolding of hFGF1 using a wide array of biophysical and biochemical techniques. Systematic analyses of the thermal and chemical denaturation data on hFGF1 variants (Q54P, K126N, R136E, K126N/R136E, Q54P/K126N, Q54P/R136E, and Q54P/K126N/R136E) indicate that nullification of charges in the heparin-binding pocket can significantly increase the stability of wtFGF1. Triple variant (Q54P/K126N/R136E) was found to be the most stable of all the hFGF1 variants studied. With the exception of triple variant, thermal unfolding of wtFGF1 and the other variants is irreversible. Thermally unfolded triple variant refolds completely to its biologically native conformation. Microsecond-level molecular dynamic simulations reveal that a network of hydrogen bonds and salt bridges linked to Q54P, K126N, and R136E mutations, are responsible for the high stability and reversibility of thermal unfolding of the triple variant. In our opinion, the findings of the study provide valuable clues for the rational design of a stable hFGF1 variant that exhibits potent wound healing properties.